sai lab

The System &Artificial Intelligence (SAI) lab focuses on exploring the field where deep learning and hardware system intersect. Our primary goal is to co-optimize AI algorithms and the underlying hardware architecture to enhance the implementation of AI. Additionally, we leverage AI as a powerful tool to streamline the hardware design process.

 

If you are interested in working with us, please send your CV to sailabapplication@gmail.com.

• Khushi Sharma (EE) 
• Hongyi Zeng (EE) 

• Mingzhi Zhu (EE)

• Ziqi Wang (EE) 

• Yutong Wang (EE)
• Fengze Yu (EE)

• Xingyu Liu (EE)

• Yunhai Hu (CS) 

• Rahul Raman (CS)

• Shawn Yin (CS)

• Qiance Tang (CS)

If you are NYU students and interested in working with me, please contact me directly:)

• Yanzhou Tang
• Shuo Xin
• Kedong Xiu

 

Yixuan Luo (Joined University of Chicago CS as a PhD student)

Chao Gao (Joined UC Riverside ECE as a PhD student)

Tianhua Xia (Joined New York University ECE as a PhD student)

Jingyang Xiang (Joined ByteDance a research engineer)

Jiajun Qin (Joined CUHK as a PhD student)

Zhenyuan Dong (EE) (Joined Purdue as a PhD student)

I am always taking undergrads/interns (can be remote) to work on the AI accelerator, efficient AI and AI privacy:), each intern will be supervised by me directly, most of them will end up with a top conference submission by the end of the internship.